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Association between the lean-to-fat mass ratio and depressive symptoms in adult Peruvian population: A cross-sectional analysis

Guerra Valencia J.; Hernández-Vásquez A.; Vargas-Fernández R. · Journal of Affective Disorders Reports (2025) · DOI: 10.1016/j.jadr.2024.100868

Resumen

Background: Previous studies on the relationship between body composition and depressive symptoms have focused on fat or lean mass separately. We aimed to examine the association between the lean-to-fat mass ratio (LFMR) and depressive symptoms in the adult Peruvian population. Methods: This cross-sectional study used the Peruvian Demographic and Health Survey 2023. Adults aged 18–59 years were included, while pregnant women and individuals with implausible anthropometric measurements were excluded. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), while the exposure variable, the LFMR, was calculated using validated regression equations derived from the National Health and Nutrition Examination Survey (NHANES) database, which included the Latino population. Nested regression models assessed the relationship between the LFMR and depressive symptoms, including linear and quadratic terms. Models were adjusted for sociodemographic, health, and behavioral factors. Marginal effects of LFMR were plotted. Results: 24,674 subjects were included. A non-linear association between LFMR and depressive symptoms, with a J-shaped curve was found. An initial decrease in depressive symptoms score with increasing LFMR was observed in the adjusted model (β: −1.89; 95 %CI: −2.24, −1.54), followed by an increase in PHQ-9 score at higher LFMR values (β: 0.23; 95 %CI: 0.18, 0.28). Limitations: Lean and fat mass were estimated via equations rather than direct measurements. Conclusions: These results underscore a non-linear association between the LFMR and depressive symptoms among Peruvian adults. An optimal balance between lean and fat mass, rather than focusing solely on one component, may be crucial in reducing depressive symptoms.

Instituciones: Universidad Científica del Sur; Universidad San Ignacio de Loyola; Universidad Privada del Norte